AFSC RACE Groundfish and Shellfish Survey Public Data
This code is primarily maintained by:
Emily Markowitz (Emily.Markowitz AT noaa.gov; @EmilyMarkowitz-NOAA)
Research Fisheries Biologist
Bering Sea Groundfish Survey Team
Alaska Fisheries Science Center,
National Marine Fisheries Service,
National Oceanic and Atmospheric Administration,
Seattle, WA 98195
Cite this data
Use the below bibtext citation, as cited in our group’s citation repository for citing the data from this data portal (NOAA Fisheries Alaska Fisheries Science Center, 2023). Add “note = {Accessed: mm/dd/yyyy}” to append the day this data was accessed.
## @misc{FOSSAFSCData,
## author = {{NOAA Fisheries Alaska Fisheries Science Center}},
## year = {2023},
## title = {Fisheries One Stop Shop Public Data: RACE Division Bottom Trawl Survey Data Query},
## howpublished = {https://www.fisheries.noaa.gov/foss/f?p=215:28:2283554735243:::::},
## publisher = {{U.S. Dep. Commer.}},
## copyright = {Public Domain}
## }The code is in development. Refer to releases for finalized products. These data were last ran and pushed to the AFSC oracle on January 25, 2023. This is not the date that these data were pulled into FOSS and the FOSS dataset may be behind.
Metadata
Data description (short)
This dataset includes zero-filled (presence and absence) observations and catch-per-unit-effort (CPUE) estimates for most identified species at a standard set of stations in the northern Bering Sea (NBS), eastern Bering Sea (EBS), Gulf of Alaska (GOA), Aleutian Islands (AI), Bering Sea Slope (BSS) Surveys conducted by the Resource Assessment and Conservation Engineering Division (RACE) Groundfish Assessment Program (GAP) oThere are no legal restrictions on access to the data.The data from this dataset are shared on the Fisheries One Stop Stop (FOSS) platform (https://www.fisheries.noaa.gov/foss/f?p=215:28:2283554735243:::::).The GitHub repository for the scripts that created this code can be found at https://github.com/afsc-gap-products/gap_public_data.For more information about codes used in the tables, please refer to the survey code books (https://www.fisheries.noaa.gov/resource/document/groundfish-survey-species-code-manual-and-data-codes-manual).These data were last updated January 25, 2023.
Data description (long)
The Resource Assessment and Conservation Engineering Division (RACE) Groundfish Assessment Program (GAP) of the Alaska Fisheries Science Center (AFSC) conducts fisheries-independent bottom trawl surveys to monitor the condition of the demersal fish and crab stocks of Alaska. These data are developed to describe the temporal distribution and abundance of commercially and ecologically important groundfish species, examine the changes in the species composition of the fauna over time and space, and describe the physical environment of the groundfish habitat.
There are no legal restrictions on access to the data. They reside in the public domain and can be freely distributed. Users must read and fully comprehend the metadata prior to use. Data should not be used beyond the limits of the source scale. Acknowledgement of NOAA, as the source from which these data were obtained, in any publications and/or other representations of these data, is suggested. These data are compiled and approved annually after each summer survey season. The data from previous years are unlikely to change substantially once published.
These data are zero-filled (presence and absence) observations from surveys conducted on fishing vessels. These surveys monitor trends in distribution and abundance of groundfish, crab, and bottom-dwelling species in Alaska’s marine ecosystems. These data include estimates of catch-per-unit-effort (CPUE) for most identified species at a standard set of stations. Some survey data are excluded, such as non-standard stations, surveys completed in earlier years using different/non-standard gear, and special tows and non-standard data collections.
Though not included in the public data, these surveys also collect oceanographic and environmental data, and biological data such as length, weight, stomach contents (to learn more about diet), otoliths (fish ear bones to learn about age), and tissue samples for genetic analysis, all of which can be shared upon special request. Also not included in the public data are estimated biomass (average total weight of all fish and crabs sampled) of crabs and groundfish that support the creation of annual stock assessments.
Bottom trawl surveys and regions
- Eastern Bering Sea Shelf (EBS) (Markowitz et al., 2022)
- Annual
- Fixed stations at center of 20 x 20 nm grid
- Northern Bering Sea (NBS) (Markowitz et al., 2022)
- Biennial/Annual
- Fixed stations at center of 20 x 20 nm grid
- Eastern Bering Sea Slope (BSS) (Hoff, 2016)
- Intermittent (funding dependent)
- Modified Index-Stratified Random of Successful Stations Survey Design
- Aleutian Islands (AI) (Von
Szalay and Raring, 2020)
- Triennial (1990s)/Biennial since 2000 in even years
- Modified Index-Stratified Random of Successful Stations Survey Design
- Gulf of Alaska (GOA) (Von
Szalay and Raring, 2018)
- Triennial (1990s)/Biennial since 2001 in odd years
- Stratified Random Survey Design
Relevant technical memorandums
User resources
- AFSC’s Resource Assessment and Conservation Engineering Division.
- For more information about codes used in the tables, please refer to the survey code books (Resource Assessment and Division, 2021).
- Find past reports about these surveys.
- GitHub repository.
- Learn more about other Research Surveys conducted at AFSC.
Access constraints
There are no legal restrictions on access to the data. They reside in the public domain and can be freely distributed.
User Constraints: Users must read and fully comprehend the metadata prior to use. Data should not be used beyond the limits of the source scale. Acknowledgement of AFSC Groundfish Assessment Program, as the source from which these data were obtained, in any publications and/or other representations of these data, is suggested.
Address: Alaska Fisheries Science Center (AFSC)
National Oceanic and Atmospheric Administration (NOAA)
Resource Assessment and Conservation Engineering Division (RACE)
Groundfish Assessment Program (GAP) 7600 Sand Point Way, N.E. bldg.
4
Seattle, WA 98115 USA
General questions and more specific data requests can be sent to afsc.gap.metadata@noaa.gov or submitted as an issue on our GitHub Organization. The version of this data used for stock assessments can be found through the Alaska Fisheries Information Network (AKFIN). For questions about the eastern Bering Sea surveys, contact Duane Stevenson (Duane.Stevenson@noaa.gov). For questions about the Gulf of Alaska or Aleutian Islands surveys, contact Ned Laman (Ned.Laman@noaa.gov). For questions specifically about crab data in any region, contact Mike Litzow (Mike.Litzow@noaa.gov), the Shellfish Assessment Program lead.
For questions, comments, and concerns specifically about the Fisheries One Stop Shop (FOSS) platform, please contact us using the Comments page on the FOSS webpage.
Column-level metadata
| Column name from data | Descriptive Column Name | Units | Description |
|---|---|---|---|
| year | Year | numeric | Year the survey was conducted in. |
| srvy | Survey | Abbreviated text | Abbreviated survey names. The column ‘srvy’ is associated with the ‘survey’ and ‘survey_id’ columns. Northern Bering Sea (NBS), Southeastern Bering Sea (EBS), Bering Sea Slope (BSS), Gulf of Alaska (GOA), Aleutian Islands (AI). |
| survey | Survey Name | text | Name and description of survey. The column ‘survey’ is associated with the ‘srvy’ and ‘survey_id’ columns. |
| survey_id | Survey ID | ID code | This number uniquely identifies a survey. Name and description of survey. The column ‘survey_id’ is associated with the ‘srvy’ and ‘survey’ columns. For a complete list of surveys, review the [code books](https://www.fisheries.noaa.gov/resource/document/g |
| cruise | Cruise ID | ID code | This is a six-digit number identifying the cruise number of the form: YYYY99 (where YYYY = year of the cruise; 99 = 2-digit number and is sequential; 01 denotes the first cruise that vessel made in this year, 02 is the second, etc.). |
| haul | Haul Number | ID code | This number uniquely identifies a sampling event (haul) within a cruise. It is a sequential number, in chronological order of occurrence. |
| hauljoin | hauljoin | ID Code | This is a unique numeric identifier assigned to each (vessel, cruise, and haul) combination. |
| stratum | Stratum ID | ID Code | RACE database statistical area for analyzing data. Strata were designed using bathymetry and other geographic and habitat-related elements. The strata are unique to each survey series. Stratum of value 0 indicates experimental tows. |
| station | Station ID | ID code | Alpha-numeric designation for the station established in the design of a survey. |
| vessel_name | Vessel Name | text | Name of the vessel used to collect data for that haul. The column ‘vessel_name’ is associated with the ‘vessel_id’ column. Note that it is possible for a vessel to have a new name but the same vessel id number. For a complete list of vessel ID codes, revi |
| vessel_id | Vessel ID | ID Code | ID number of the vessel used to collect data for that haul. The column ‘vessel_id’ is associated with the ‘vessel_name’ column. Note that it is possible for a vessel to have a new name but the same vessel id number. For a complete list of vessel ID codes, |
| date_time | Date and Time of Haul | MM/DD/YYYY HH::MM | The date (MM/DD/YYYY) and time (HH:MM) of the beginning of the haul. |
| latitude_dd_start | Start Latitude (decimal degrees) | decimal degrees, 1e-05 resolution | Latitude (one hundred thousandth of a decimal degree) of the start of the haul. |
| longitude_dd_start | Start Longitude (decimal degrees) | decimal degrees, 1e-05 resolution | Longitude (one hundred thousandth of a decimal degree) of the start of the haul. |
| latitude_dd_end | End Latitude (decimal degrees) | decimal degrees, 1e-05 resolution | Latitude (one hundred thousandth of a decimal degree) of the end of the haul. |
| longitude_dd_end | End Longitude (decimal degrees) | decimal degrees, 1e-05 resolution | Longitude (one hundred thousandth of a decimal degree) of the end of the haul. |
| species_code | Taxon Code | ID code | The species code of the organism associated with the ‘common_name’ and ‘scientific_name’ columns. For a complete species list, review the [code books](https://www.fisheries.noaa.gov/resource/document/groundfish-survey-species-code-manual-and-data-codes-ma |
| itis | ITIS Taxonomic Serial Number | ID code | Species code as identified in the Integrated Taxonomic Information System (https://itis.gov/). Codes were last updated NA. |
| worms | World Register of Marine Species Taxonomic Serial Number | ID code | Species code as identified in the World Register of Marine Species (WoRMS) (https://www.marinespecies.org/). Codes were last updated NA. |
| common_name | Taxon Common Name | text | The common name of the marine organism associated with the ‘scientific_name’ and ‘species_code’ columns. For a complete species list, review the [code books](https://www.fisheries.noaa.gov/resource/document/groundfish-survey-species-code-manual-and-data-c |
| scientific_name | Taxon Scientific Name | text | The scientific name of the organism associated with the ‘common_name’ and ‘species_code’ columns. For a complete taxon list, review the [code books](https://www.fisheries.noaa.gov/resource/document/groundfish-survey-species-code-manual-and-data-codes-manu |
| taxon_confidence | Taxon Confidence Rating | rating | Confidence in the ability of the survey team to correctly identify the taxon to the specified level, based solely on identification skill (e.g., not likelihood of a taxon being caught at that station on a location-by-location basis). Quality codes follow: |
| cpue_kgha | Weight CPUE (kg/ha) | kilograms/hectare | Relative Density. Catch weight (kilograms) divided by area (hectares) swept by the net. |
| cpue_kgkm2 | Weight CPUE (kg/km2) | kilograms/kilometers2 | Relative Density. Catch weight (kilograms) divided by area (squared kilometers) swept by the net. |
| cpue_noha | Number CPUE (no./ha) | count/hectare | Relative Abundance. Catch number (in number of organisms) per area (hectares) swept by the net. |
| cpue_nokm2 | Number CPUE (no./km2) | count/kilometers2 | Relative Abundance. Catch number (in number of organisms) per area (squared kilometers) swept by the net. |
| weight_kg | Taxon Weight (kg) | kilograms, thousandth resolution | Weight (thousandths of a kilogram) of individuals in a haul by taxon. |
| count | Taxon Count | count, whole number resolution | Total number of individuals caught in haul by taxon, represented in whole numbers. |
| bottom_temperature_c | Bottom Temperature (Degrees Celsius) | degrees Celsius, tenths of a degree resolution | Bottom temperature (tenths of a degree Celsius); NA indicates removed or missing values. |
| surface_temperature_c | Surface Temperature (Degrees Celsius) | degrees Celsius, tenths of a degree resolution | Surface temperature (tenths of a degree Celsius); NA indicates removed or missing values. |
| depth_m | Depth (m) | meters, tenths of a meter resolution | Bottom depth (tenths of a meter). |
| distance_fished_km | Distance Fished (km) | kilometers, thousandths of kilometer resolution | Distance the net fished (thousandths of kilometers). |
| net_width_m | Net Width (m) | meters | Measured or estimated distance (meters) between wingtips of the trawl. |
| net_height_m | Net Height (m) | meters | Measured or estimated distance (meters) between footrope and headrope of the trawl. |
| area_swept_ha | Area Swept (ha) | hectares | The area the net covered while the net was fishing (hectares), defined as the distance fished times the net width. |
| duration_hr | Tow Duration (decimal hr) | decimal hours | This is the elapsed time between start and end of a haul (decimal hours). |
| performance | Haul Performance Code (rating) | rating | This denotes what, if any, issues arose during the haul. For more information, review the code books. |
Access the data
While pulling data, please keep in mind that this is a very large file. For reference:
## RACEBASE_FOSS.FOSS_CPUE_ZEROFILLED:
## rows: 36317744
## cols: 37
## 9.742 GBAccess data interactively through the FOSS platform
Select, filter, and package this and other NOAA Fisheries data from
the Fisheries
One Stop Shop (FOSS) platform. This user-friendly portal is
maintained through Oracle APEX. A useful intro to using
APIs in R can be found here. A user
guide for the FOSS platform can be found here.
Connect to the API with R
# install.packages(c("httr", "jsonlite"))
library("httr")
library("jsonlite")
# link to the API
api_link <- "https://apps-st.fisheries.noaa.gov/ods/foss/afsc_groundfish_survey/"Select all data
res <- httr::GET(url = api_link)
# res # Test connection
data <- jsonlite::fromJSON(base::rawToChar(res$content))
# names(data)
knitr::kable(head(data$items, 3)) | year | srvy | survey | survey_id | cruise | haul | stratum | station | vessel_name | vessel_id | date_time | latitude_dd | longitude_dd | species_code | common_name | scientific_name | taxon_confidence | cpue_kgha | cpue_kgkm2 | cpue_kg1000km2 | cpue_noha | cpue_nokm2 | cpue_no1000km2 | weight_kg | count | bottom_temperature_c | surface_temperature_c | depth_m | distance_fished_km | net_width_m | net_height_m | area_swept_ha | duration_hr | tsn | ak_survey_id | links |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2002 | AI | Aleutian Islands Bottom Trawl Survey | 5.2E+001 | 2.00201E+005 | 6.0E+000 | 7.22E+002 | 307-63 | Vesteraalen | 9.4E+001 | 05/17/2002 18:56:58 | 5.3737209999999997E+001 | -1.6701570000000001E+002 | 9.502E+004 | feathery bryozoan | Eucratea loricata | Low | 1.7493999999999999E-002 | 1.7494449999999999E+000 | 1.7494451079999999E+003 | NA | NA | NA | 4.3999999999999997E-002 | 0 | 4.0999999999999996E+000 | 5.2999999999999998E+000 | 1.87E+002 | 1.5609999999999999E+000 | 1.6111999999999998E+001 | 7.25E+000 | 2.5150831999999994E+000 | 2.8000000000000003E-001 | 155809 | 878821 | self , https://apps-st.fisheries.noaa.gov/ods/foss/afsc_groundfish_survey/878821 |
| 2002 | AI | Aleutian Islands Bottom Trawl Survey | 5.2E+001 | 2.00201E+005 | 6.0E+000 | 7.22E+002 | 307-63 | Vesteraalen | 9.4E+001 | 05/17/2002 18:56:58 | 5.3737209999999997E+001 | -1.6701570000000001E+002 | 7.9E+004 | squid unid. | Decapodiformes | High | 2.2266000000000001E-002 | 2.2265670000000002E+000 | 2.2265665009999998E+003 | 3.180809E+000 | 3.1808092900000003E+002 | 3.1808092869500001E+005 | 5.6000000000000001E-002 | 8.0E+000 | 4.0999999999999996E+000 | 5.2999999999999998E+000 | 1.87E+002 | 1.5609999999999999E+000 | 1.6111999999999998E+001 | 7.25E+000 | 2.5150831999999994E+000 | 2.8000000000000003E-001 | NA | 878822 | self , https://apps-st.fisheries.noaa.gov/ods/foss/afsc_groundfish_survey/878822 |
| 2002 | AI | Aleutian Islands Bottom Trawl Survey | 5.2E+001 | 2.00201E+005 | 6.0E+000 | 7.22E+002 | 307-63 | Vesteraalen | 9.4E+001 | 05/17/2002 18:56:58 | 5.3737209999999997E+001 | -1.6701570000000001E+002 | 2.4191E+004 | shortfin eelpout | Lycodes brevipes | High | 3.5784000000000003E-002 | 3.5784099999999999E+000 | 3.5784104480000001E+003 | 7.9520199999999996E-001 | 7.9520231999999993E+001 | 7.9520232174000004E+004 | 8.9999999999999997E-002 | 2.0E+000 | 4.0999999999999996E+000 | 5.2999999999999998E+000 | 1.87E+002 | 1.5609999999999999E+000 | 1.6111999999999998E+001 | 7.25E+000 | 2.5150831999999994E+000 | 2.8000000000000003E-001 | 165258 | 878823 | self , https://apps-st.fisheries.noaa.gov/ods/foss/afsc_groundfish_survey/878823 |
Subset data
Here, as an example, we can subset the data for the 2018 Aleutian Islands Bottom Trawl Survey.
res <- httr::GET(url = api_link, query = list(year = "2018", srvy = "AI"))
data <- jsonlite::fromJSON(base::rawToChar(res$content))
x <- data$items
x <- x[,c("srvy", "year", "stratum", "station", "vessel_name", "latitude_dd", "longitude_dd",
"species_code", "common_name", "scientific_name", "taxon_confidence",
"cpue_kgha", "cpue_noha", "weight_kg", "count",
"bottom_temperature_c", "surface_temperature_c", "depth_m")]
knitr::kable(head(x, 3))Access data via Oracle
If the user has access to the AFSC Oracle database, the
user can use SQL developer to view and pull the FOSS public
data directly from the RACEBASE_FOSS Oracle
schema.
Connect to Oracle from R
Many users will want to access the data from Oracle
using R. The user will need to install the
RODBC R package and ask OFIS (IT) connect
R to Oracle. Then, use the following code in
R to establish a connection from R to
Oracle:
Here, the user can write in their username and password directly into
the RODBC connect function. Never save usernames or
passwords in scripts that may be intentionally or unintentionally shared
with others.
library("RODBC")
# Define RODBC connection to ORACLE
channel<-odbcConnect(dsn = "AFSC",
uid = "USERS_USERNAME", # change
pwd = "USERS_PASSWORD", # change
believeNRows = FALSE)
odbcGetInfo(channel) # Execute the connectionOr have the script prompt the user for the connection info. Here, pop-ups will appear on the screen asking for the username and password.
library("RODBC")
library("getPass")
# Define RODBC connection to ORACLE
get.connected <- function(schema='AFSC'){(echo=FALSE)
username <- getPass(msg = "Enter your ORACLE Username: ")
password <- getPass(msg = "Enter your ORACLE Password: ")
channel <- RODBC::odbcConnect(paste(schema),paste(username),paste(password),
believeNRows=FALSE)
}
channel <- get.connected() # Execute the connectionSelect all data
Once connected, pull and save (if needed) the table into the
R environment.
# pull table from oracle into R environment
a <- RODBC::sqlQuery(channel, "SELECT * FROM RACEBASE_FOSS.FOSS_CPUE_ZEROFILLED")
# Save table to local directory
write.csv(x = a, file = "RACEBASE_FOSS-FOSS_CPUE_ZEROFILLED.csv")Subset data
To pull a small subset of the data (especially since files like
RACEBASE_FOSS.FOSS_CPUE_ZEROFILLED are so big), use a
variation of the following code. Here, we are pulling EBS Pacific cod
from 2010 - 2021:
# Pull data
a <- RODBC::sqlQuery(channel, "SELECT * FROM RACEBASE_FOSS.FOSS_CPUE_ZEROFILLED
WHERE SRVY = 'EBS'
AND COMMON_NAME = 'Pacific cod'
AND YEAR >= 2010
AND YEAR < 2021")
# Save table to local directory
write.csv(x = a, file = "RACEBASE_FOSS-FOSS_CPUE_ZEROFILLED-ebs_pcod_2010-2020.csv")Join catch and haul data
If this file is too large, you can join catch and haul data. Pull the
RACEBASE_FOSS.JOIN_FOSS_CPUE_CATCH and
RACEBASE_FOSS.JOIN_FOSS_CPUE_HAUL tables, which are much
smaller, and combine the table locally yourself.
The full join the JOIN_FOSS_CPUE_CATCH and JOIN_FOSS_CPUE_HAUL datasets using HAULJOIN to create zero-filled (presence and absence) observations and catch-per-unit-effort (CPUE) estimates for all identified species at a standard set of stations in the northern Bering Sea (NBS), eastern Bering Sea (EBS), Gulf of Alaska (GOA), Aleutian Islands (AI), Bering Sea Slope (BSS) Surveys conducted by the Resource Assessment and Conservation Engineering Division (RACE) Groundfish Assessment Program (GAP) oThere are no legal restrictions on access to the data.The data from this dataset are shared on the Fisheries One Stop Stop (FOSS) platform (https://www.fisheries.noaa.gov/foss/f?p=215:28:2283554735243:::::).The GitHub repository for the scripts that created this code can be found at https://github.com/afsc-gap-products/gap_public_data.For more information about codes used in the tables, please refer to the survey code books (https://www.fisheries.noaa.gov/resource/document/groundfish-survey-species-code-manual-and-data-codes-manual).These data were last updated January 25, 2023.
## RACEBASE_FOSS.JOIN_FOSS_CPUE_CATCH:
## rows: 36317744
## cols: 14
## 2.641 GB## RACEBASE_FOSS.JOIN_FOSS_CPUE_HAUL:
## rows: 31608
## cols: 24
## 0.006 GBSuggestions and comments
If the data or metadata can be improved, please create a pull request, submit an issue to the GitHub organization, submit an issue to the code’s repository, reach out the the survey team leads (listed above), or to Fisheries One Stop Shop (FOSS) platform managers.
R version metadata
This data was compiled using the below R environment and
R packages:
sessionInfo()## R version 4.2.2 (2022-10-31 ucrt)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## Running under: Windows 10 x64 (build 19045)
##
## Matrix products: default
##
## locale:
## [1] LC_COLLATE=English_United States.utf8 LC_CTYPE=English_United States.utf8 LC_MONETARY=English_United States.utf8
## [4] LC_NUMERIC=C LC_TIME=English_United States.utf8
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] RODBC_1.3-20 jsonlite_1.8.4 httr_1.4.4 knitr_1.41 badger_0.2.2 stringr_1.5.0 taxize_0.9.100 janitor_2.1.0
## [9] rmarkdown_2.19 readr_2.1.3 magrittr_2.0.3 dplyr_1.0.10 tidyr_1.2.1
##
## loaded via a namespace (and not attached):
## [1] sass_0.4.4 bit64_4.0.5 vroom_1.6.0 foreach_1.5.2 bold_1.2.0 here_1.0.1
## [7] bslib_0.4.2 assertthat_0.2.1 askpass_1.1 BiocManager_1.30.19 rvcheck_0.2.1 highr_0.10
## [13] yulab.utils_0.0.6 yaml_2.3.6 pillar_1.8.1 lattice_0.20-45 glue_1.6.2 uuid_1.1-0
## [19] digest_0.6.31 RColorBrewer_1.1-3 snakecase_0.11.0 colorspace_2.0-3 htmltools_0.5.4 plyr_1.8.8
## [25] pkgconfig_2.0.3 httpcode_0.3.0 gitcreds_0.1.2 purrr_1.0.1 scales_1.2.1 tzdb_0.3.0
## [31] openssl_2.0.5 timechange_0.1.1 tibble_3.1.8 generics_0.1.3 ggplot2_3.4.0 usethis_2.1.6
## [37] ellipsis_0.3.2 cachem_1.0.6 withr_2.5.0 credentials_1.3.2 cli_3.6.0 crayon_1.5.2
## [43] evaluate_0.19 fs_1.5.2 fansi_1.0.3 nlme_3.1-161 xml2_1.3.3 gh_1.3.1
## [49] tools_4.2.2 data.table_1.14.6 hms_1.1.2 gert_1.9.2 lifecycle_1.0.3 munsell_0.5.0
## [55] compiler_4.2.2 jquerylib_0.1.4 rlang_1.0.6 grid_4.2.2 conditionz_0.1.0 sys_3.4.1
## [61] iterators_1.0.14 rstudioapi_0.14 gtable_0.3.1 codetools_0.2-18 DBI_1.1.3 reshape_0.8.9
## [67] curl_4.3.3 readtext_0.81 R6_2.5.1 zoo_1.8-11 lubridate_1.9.0 fastmap_1.1.0
## [73] bit_4.0.5 utf8_1.2.2 rprojroot_2.0.3 dlstats_0.1.6 ape_5.6-2 stringi_1.7.8
## [79] parallel_4.2.2 crul_1.3 Rcpp_1.0.9 vctrs_0.5.1 tidyselect_1.2.0 xfun_0.36NOAA README
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